Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis

There is widespread concern that environmental factor may not be playing a pivotal role in influencing the generation performance of solar photovoltaic (PV) plants. The aim of this paper is to provide a fair and impartial operational performance evaluation of solar PV power plants taking into account of the impacts of environmental factors from real field data. Stochastic frontier analysis (SFA) is used to attribute the impacts of environmental factors (temperature, cloud amount, elevation, wind speed and precipitation) on inputs (like insolation and daylight hours) of solar PV power plants; while data envelopment analysis (DEA) is used to compute the environment-adjusted operational efficiency of these plants. SFA is utilized in the adjustment process for its merit of separating statistical noise from the error term, and DEA is used for its advantage of capturing the interaction among multiple inputs and outputs in a scalar value. The empirical analysis shows that the average operational efficiency of 70 grid-connected solar PV power plants in the United States slightly declines after accounting the impacts of environmental factors and statistical noise. Finally, the results partially support the initial concern from the statistical perspective and temperature is found to be the most significant influencing environmental factor, while precipitation and wind speed show no significant influence on operational efficiency. Therefore, the necessity of accounting for the impacts of environmental factors in the performance evaluation of solar PV power plants should not be omitted.